Modern Development Trends Hospitality Industry of the South of Russia

This study is aimed at analyzing the features of the functioning of the hospitality industry in the South of Russia. The authors gave a brief description of the Southern Federal District, analyzed the quantitative indicators of collective accommodation facilities, the total number of rooms in hotels and rooms of the highest category in hotels and similar accommodation facilities over the past five years. The study revealed the degree of impact on the hospitality industry of the analyzed region of the pandemic caused by COVID-19, analyzed the income from the services provided by collective accommodation facilities of the Southern Federal District, including the republics of Adygea, Kalmykia, Crimea, Krasnodar Territory, Astrakhan, Volgograd, Rostov regions and the federal city of Sevastopol. The study includes statistics on the number of citizens of the Russian Federation and foreign citizens accommodated in collective accommodation facilities, the average number of employees of hospitality industry enterprises. The analysis made it possible to develop recommendations for improving the activities of city hotels and suburban accommodation facilities through the use of new, more efficient sales channels, the introduction of personalization using CRM systems, expanding the list of additional services that make it possible to develop comprehensive tourist offers such as weekend tours, which will allow if you do not provide new jobs, then save the existing ones, contribute to preventing the closure of business in the hospitality industry, thereby maintaining the standard of living in the district by maintaining the income of the population and preserving the income of local budgets. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

The Impact of Marketing Mix Elements on Tourist's Satisfaction towards Five Stars Hotel Services in Dubai during COVID-19

Purpose: Tourist satisfaction measures the prosperity of a business and tourism sector. If there are many satisfied tourists, the tourism sector will profit, but if there are many less satisfied tourists, the tourism sector will lose money. Therefore, it is necessary to know the factors that affect tourist satisfaction. This study aims to develop and implement a method for five-star hotels to identify attributes that will increase tourists' satisfaction during the pandemic. Method: The study used 100 tourists in Dubai as respondents who were selected randomly at five-star hotels. The results showed no impact of all marketing mix elements on tourist satisfaction except the physical evidence of the COVID-19 pandemic. Outcomes: The results of this study indicated that the COVID-19 pandemic influenced five-star hotel services in Dubai and that the marketing mix elements used by the hotels are an important factor in tourist satisfaction. In conclusion, Dubai must understand the importance of a marketing mix to fulfil tourist satisfaction and improve the service that makes it more significant in the tourism industry. Originality: Numerous modifying variables impacting the management process have been examined in the literature on complaint management. It is the first study investigating the five-star hotel in Dubai to check the operative services on how to work on tourist satisfaction and determine the impact of marketing mix elements on tourism during the pandemic. © 2023, ASERS Publishing House. All rights reserved.

A Smart Framework to Analyze Hotel Services after COVID-19

In the last decade, many websites have allowed customers to provide reviews about their experiences in dealing with different hotels like describing their opinions about different sides like cleanliness, food, employees, and other services. However, after COVID-19, new concerns have emerged linked to the health precautionary and preventive processes. At the same time, the amount of generated data (Textual Data) has become very huge (Big Data), and it needs to auto classifier for processing it where it is impossible to review manually. So, this research proposed a smart method to detect useful information from text by extracting the interesting services from comments automatically. The method depended on machine learning (ML) and compared between five different classification models (Spacy, Naïve Bayes (NB), Stochastic Gradient Descent (SGD), Passive Aggressive, and AdaBoost) to determine which one provides the best results and accuracy. According to the experiment on a real dataset containing more than 1000 records, the NB was the best accurate with 98%, while the Spacy was less and that related to the small size of training data. © 2022 Bharati Vidyapeeth, New Delhi.

Evaluation of Hotel Services Quality by booking.com Users and Organizational Activities Undertaken by Managers – Lublin Case Study

The aim of this study is to present the correlation between guests’ evaluations and opinions about the quality of hotel services and decisions made by managers of selected hotels in Lublin. The results of the search indicate that three-star hotels predominate in the city, therefore the study focused on objects of this category. Several methods were used in the research procedure, including Internet query of hotel websites, the contextual analysis method, which is the equivalent of Text Mining, in the field of analyzing comments left on the booking.com portal and a diagnostic survey using an interview questionnaire addressed to hotel managers. In terms of quantitative assessment (on a scale of 1–10), of the hotels in Lublin included (Focus, Locomotiva, Victoria and Willowa), the Focus Hotel was rated highest (mean score of 8.8). Considering all hotels, in qualitative assessment, the following variables received the most positive opinions: level of service and cleanliness of room (in Focus, Victoria and Locomotiva hotels), location (in Victoria Hotel). Almost half of all negative comments concerned the parking area. The survey conducted with managers shows that the comments of guests have a large influence on the changes implemented in the hotels (e.g., breakfast serving time in Willowa Hotel or extension of buffet offer in Locomotiva Hotel). The contextual analysis method, which can be equivalent to the SERVQUAL method, is of particular research value especially under the conditions of the COVID-19 pandemic when it is impossible to conduct interviews in person. © 2021 Wydawnictwo Uniwersytetu Marii Curie-Sklodowskiej w Lublinie. All rights reserved.

Integrating Chaotic Perspective and Behavioral Learning Theory into a Global Pandemic Crisis Management Framework for Hotel Service Providers

Hotel service providers are among the most affected by the evolving Covid-19 pandemic. Although the consequences of the pandemic on hotel operations have been widely examined, the question of how hotel businesses can revive, innovate, and transform in order to survive and recover remains vastly under-researched. This study aims to provide insights on this important topic by analyzing 312 news articles between December 1, 2019, and March 1, 2021, published by global news media, which report hotels' strategies and tactics to deal with the pandemic. Grounded on chaos theory, behavioral learning theory, and an integrated crisis management model, a global pandemic crisis management framework is developed. Practically, the paper reveals best practices applied by hoteliers to deal with the pandemic (e.g., service transformation, smart marketing, strategic collaboration/alliance, mergers and acquisitions, and digitalization) and suggests ways for hotel services providers to adapt to the "new travel" age.